• B. Deepthi Reddy
• G. Yogitha
• C. Anirudh Jayant
• D. Goutham

Land mark classification and detection is useful in many social sharing websites and search engines to extract relevant data on given input image. Recent research in object recognition has used such sites as a source of image data, but the test images have been selected and labeled by hand, yielding relatively small validation sets. In this paper we study image classification on a much larger dataset of 30 million images, including nearly 2 million of which have been labeled into one of 500 categories. The dataset and categories are formed automatically from geotagged photos from Flickr, by looking for peaks in the spatial geotag distribution corresponding to frequently-photographed landmarks. We learn models for these landmarks with cloud vision API.

Object detection, Vision API, Geotagged photos.

"Land Mark Recognition Through Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 2, page no.119-123, February 2020, Available :http://www.jetir.org/papers/JETIR2002424.pdf

"Land Mark Recognition Through Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 2, page no. pp119-123, February 2020, Available at : http://www.jetir.org/papers/JETIR2002424.pdf